- Thread starter andru4u
- Start date

If you want to check the robustness of your original result, you should take many (i.e., 100 or more) random subsets of n=10 from each group, and for each of these random subsets of n=10, do a t-test, then see how many t-tests have a significant p-value. In other words, do many t-tests of n=10 vs n=10....

Is there another established way of testing for robustness that can be applied to my problem... thanks

http://ssc.utexas.edu/consulting/answers/general/gen26.html

so you can follow my previous advice, but use this test instead of a t-test

I am not sure if I have answered your question about 'replacement'... the answer I gave is with a layman's understanding of what replacement is.

The way you estimate a population's variance from a sample depends on if you sample with replacement or not. But I think this is a moot point, given what has been said above.